forecast.lm is used to predict linear models, especially those
involving trend and seasonality components.
# S3 method for lm forecast(object, newdata, h = 10, level = c(80, 95), fan = FALSE, lambda = object$lambda, biasadj = NULL, ts = TRUE, ...)
An optional data frame in which to look for variables with
which to predict. If omitted, it is assumed that the only variables are
trend and season, and
Number of periods for forecasting. Ignored if
Confidence level for prediction intervals.
Box-Cox transformation parameter. If
Use adjusted back-transformed mean for Box-Cox transformations. If transformed data is used to produce forecasts and fitted values, a regular back transformation will result in median forecasts. If biasadj is TRUE, an adjustment will be made to produce mean forecasts and fitted values.
Other arguments passed to
An object of class "
summary is used to obtain and print a summary of the
results, while the function
plot produces a plot of the forecasts and
The generic accessor functions
extract useful features of the value returned by
An object of class
"forecast" is a list containing at least the
A list containing information about the fitted model
The name of the forecasting method as a character string
Point forecasts as a time series
Lower limits for prediction intervals
Upper limits for prediction intervals
The confidence values associated with the prediction intervals
The historical data for the response variable.
Residuals from the fitted model. That is x minus fitted values.
forecast.lm is largely a wrapper for
predict.lm() except that it allows variables "trend"
and "season" which are created on the fly from the time series
characteristics of the data. Also, the output is reformatted into a